import os

data_dir = os.getcwd() + '/../data/food/'
train_dir = data_dir + 'train.npz'
test_dir = data_dir + 'test.npz'
files = ['train', 'test']
exp_dir = os.getcwd() + '/experiments/food/'
log_dir = exp_dir + 'train.log'
model_dir = exp_dir + 'model.pth'
case_dir = os.getcwd() + '/case/bad_case.txt'
vocab_path = data_dir + 'vocab.npz'

max_vocab_size = 1000000

n_split = 5
dev_split_size = 0.1
batch_size = 32
embedding_size = 128
hidden_size = 384
drop_out = 0.5
lr = 0.001
betas = (0.9, 0.999)
lr_step = 5
lr_gamma = 0.8

epoch_num = 30
min_epoch_num = 5
patience = 0.0002
patience_num = 5

gpu = '0'

# label for food
labels = ['food', 'nutrient', 'disease', 'crowd',
          'organ']

# label2id for food
label2id = {
    "O": 0,
    "B-food": 1,
    "B-nutrient": 2,
    'B-disease': 3,
    'B-crowd': 4,
    'B-organ': 5,
    "I-food": 6,
    "I-nutrient": 7,
    'I-disease': 8,
    'I-crowd': 9,
    'I-organ': 10,
    "S-food": 11,
    "S-nutrient": 12,
    'S-disease': 13,
    'S-crowd': 14,
    'S-organ': 15,
}

id2label = {_id: _label for _label, _id in list(label2id.items())}
